Abstract: Systems/techniques that facilitate deep learning multi-planar reformatting of medical images are provided. In various embodiments, a system can access a three-dimensional medical image. In various aspects, the system can localize, via execution of a machine learning model, a set of landmarks depicted in the three-dimensional medical image, a set of principal anatomical planes depicted in the three-dimensional medical image, and a set of organs depicted in the three-dimensional medical image. In various instances, the system can determine an anatomical orientation exhibited by the three-dimensional medical image, based on the set of landmarks, the set of principal anatomical planes, or the set of organs. In various cases, the system can rotate the three-dimensional medical image, such that the anatomical orientation now matches a predetermined anatomical orientation.

Abstract: The current disclosure provides systems and methods for automatic image alignment of three-dimensional (3D) medical image volumes. The method includes pre-processing the 3D medical image volume by selecting a sub-volume of interest, detecting anatomical landmarks in the sub-volume using a deep neural network, estimating transformation parameters based on the anatomical landmarks to adjust rotation angles and translation of the sub-volume, adjusting the rotation angles and translation to produce a first aligned sub-volume, determining confidence in the transformation parameters based on the first aligned sub-volume, and iteratively refining the transformation parameters if the confidence is below a predetermined threshold. The disclosed approach for automated image alignment reduces the need for manual alignment and, increases a probability of the 3D image volume converging to a desired orientation compared to conventional approaches.

Abstract: Methods and systems are provided for adaptive scan control. In one embodiment, a method for an imaging system includes performing, with the imaging system, a first contrast scan of a subject including injection of a contrast agent to the subject; processing projection data of the subject acquired during the first contrast scan to measure a contrast signal of the subject at a monitoring area; estimating a target acquisition timing for a first acquisition of a second contrast scan of the subject based on the contrast signal; and performing, with the imaging system, the second contrast scan of the subject, with the first acquisition performed at the target acquisition timing and without performing any monitoring scans between the first contrast scan and the second contrast scan.

Abstract: Systems/techniques that facilitate deep learning multi-planar reformatting of medical images are provided. In various embodiments, a system can access a three-dimensional medical image. In various aspects, the system can localize, via execution of a machine learning model, a set of landmarks depicted in the three-dimensional medical image, a set of principal anatomical planes depicted in the three-dimensional medical image, and a set of organs depicted in the three-dimensional medical image. In various instances, the system can determine an anatomical orientation exhibited by the three-dimensional medical image, based on the set of landmarks, the set of principal anatomical planes, or the set of organs. In various cases, the system can rotate the three-dimensional medical image, such that the anatomical orientation now matches a predetermined anatomical orientation.

Abstract: Various methods and systems are provided for generating a guided workflow and assisting in clinical decision making during operation of an imaging system at a site. Via a protocol manager interface, displaying a default protocol generated for the imaging system by a manufacturer, an authorized user may customize the protocol for the site. A workflow, in accordance with the modified protocol, is then displayed to another non-authenticated user at a time of operating the imaging system for an active scan.

Abstract: Techniques are described for automatically detecting scan characteristics of a medical image series. According to an embodiment, a system is provided that comprises a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory. The computer executable components comprise an image generation component that generates a representative image of a medical image series comprising a plurality of scan images, and a series characterization component that processes the representative image using one or more characteristic detection algorithms to determine one or more characteristics of the medical image series. The system can further tailor the visualization layout for viewing the medical image series based on the one or more characteristics and/or automatically perform various workflow tasks based on the one or more characteristics.

Abstract: Methods and systems are provided for adaptive scan control. In one embodiment, a method for a computing device communicatively coupled to an imaging system includes, selecting a scan protocol, displaying an adaptive scan protocol graphical user interface (GUI) on a display device coupled to the computing device, adjusting one or more parameters of the scan protocol in response to user input to the adaptive scan protocol GUI, updating a visual representation of the scan protocol displayed via the adaptive scan protocol GUI in correspondence to the adjustment of the one or more parameters of the scan protocol, and storing the adjusted scan protocol in memory of the computing device.

Abstract: Methods and systems are provided for adaptive scan control. In one embodiment, a method for an imaging system includes performing, with the imaging system, a first contrast scan of a subject including injection of a contrast agent to the subject; processing projection data of the subject acquired during the first contrast scan to measure a contrast signal of the subject at a monitoring area; estimating a target acquisition timing for a first acquisition of a second contrast scan of the subject based on the contrast signal; and performing, with the imaging system, the second contrast scan of the subject, with the first acquisition performed at the target acquisition timing and without performing any monitoring scans between the first contrast scan and the second contrast scan.

Abstract: Methods and systems are provided for adaptive scan control. In one embodiment, a method for a computing device communicatively coupled to an imaging system includes, selecting a scan protocol, displaying an adaptive scan protocol graphical user interface (GUI) on a display device coupled to the computing device, adjusting one or more parameters of the scan protocol in response to user input to the adaptive scan protocol GUI, updating a visual representation of the scan protocol displayed via the adaptive scan protocol GUI in correspondence to the adjustment of the one or more parameters of the scan protocol, and storing the adjusted scan protocol in memory of the computing device.

Abstract: Various methods and systems are provided for generating a guided workflow and assisting in clinical decision making during operation of an imaging system at a site. Via a protocol manager interface, displaying a default protocol generated for the imaging system by a manufacturer, an authorized user may customize the protocol for the site. A workflow, in accordance with the modified protocol, is then displayed to another non-authenticated user at a time of operating the imaging system for an active scan.

Abstract: An imaging system includes an imaging unit, a display unit, and at least one processor. The at least one processor is configured to acquire a first type of diagnostic imaging information of the patient; reconstruct a first image using the first type of diagnostic imaging information; if a first stop criterion for terminating imaging is not satisfied, acquire a second type of diagnostic imaging information having an increased level of acquisitional burden; reconstruct a second image; if a second stop criterion for terminating imaging is not satisfied, acquire a third type of diagnostic imaging information having an increased level of acquisitional burden, wherein the patient is maintained on a table of the imaging unit during the acquisition of the second type of diagnostic imaging information, reconstruction of the second image, and acquisition of the third type of diagnostic imaging information; reconstruct a third image; and display the third image.

Abstract: A computed tomography (CT) imaging system includes a CT imaging unit, a display unit and at least one processor. The CT imaging unit includes an X-ray source and a CT detector. The at least one processor is operably coupled to the imaging unit and the display unit, and is configured to: acquire at least three phases of CT imaging information via the CT imaging unit; determine timing information for imaging intensity of blood vessels represented in the CT imaging information; assign corresponding colors to the blood vessels based on the timing information; reconstruct an image using the CT imaging information from the at least three phases, wherein the blood vessels depicted in the reconstructed image are represented using the corresponding colors based on the timing information; and display the image on the display unit.

Abstract: A computed tomography (CT) imaging system includes a CT imaging unit, a display unit and at least one processor. The CT imaging unit includes an X-ray source and a CT detector. The at least one processor is operably coupled to the imaging unit and the display unit, and is configured to: acquire at least three phases of CT imaging information via the CT imaging unit; determine timing information for imaging intensity of blood vessels represented in the CT imaging information; assign corresponding colors to the blood vessels based on the timing information; reconstruct an image using the CT imaging information from the at least three phases, wherein the blood vessels depicted in the reconstructed image are represented using the corresponding colors based on the timing information; and display the image on the display unit.

Abstract: An imaging system includes an imaging unit, a display unit, and at least one processor. The at least one processor is configured to acquire a first type of diagnostic imaging information of the patient; reconstruct a first image using the first type of diagnostic imaging information; if a first stop criterion for terminating imaging is not satisfied, acquire a second type of diagnostic imaging information having an increased level of acquisitional burden; reconstruct a second image; if a second stop criterion for terminating imaging is not satisfied, acquire a third type of diagnostic imaging information having an increased level of acquisitional burden, wherein the patient is maintained on a table of the imaging unit during the acquisition of the second type of diagnostic imaging information, reconstruction of the second image, and acquisition of the third type of diagnostic imaging information; reconstruct a third image; and display the third image.